Introduction
Non-communicable diseases (NCDs), which often manifest with multiple conditions within the same patient, expose some of the inadequacies of health systems unprepared for the rapid epidemiological transition from communicable diseases to NCDs.1 2 Governments, international organisations and donors worldwide are concerned about rising costs of healthcare, coupled with inadequate performance of national health systems. Moreover, the rise in NCD burden has driven cost increases as more expensive therapies are needed for longer durations of treatment. Hence, many policymakers are concerned about improving efficiency and effectiveness of health systems.
Contrary to these looming trends, however, global health research has typically focused on single diseases, on vertical programmes in isolation and on single technical interventions (eg, introduction of new technologies like vaccines or drugs).3 As a case in point, most economic evaluations to date, including cost-effectiveness analysis research that explores both technical and allocative efficiency, have analysed single health interventions and thus operationalised the computation of total health gains (eg, total deaths averted or disability-adjusted life years averted) per total expenditure on specific interventions to identify ‘best buys’.4
New approaches in the conduct of economic evaluations are needed to help policymakers choose what may be good value (ie, greater health, distribution of health, or financial risk protection) for money (ie, per budget expenditure) investments for health system strengthening (HSS) that tend to be programmatic rather than single technical interventions. As a result, HSS interventions are more difficult to evaluate. HSS interventions that warrant evaluation include, for example, workforce training and deployment, pharmaceutical procurement and supply chain management, organisational management, cross-sectoral coordination and community-based convening. We posit that these new approaches must first consider system-wide delivery platforms (eg, district public health departments, health posts, community health workers, clinics) and operational elements (eg, community health boards, data information systems, supply chains) as units of analysis, in place of disease-focused interventions, to improve one particular platform (technical efficiency) or ration across platforms (allocative efficiency). Second, they should capture the dynamic interactions between the main interdependent components of health systems, specifically financing, delivery, individual behaviour and community decision-making, accounting for feedbacks, adaptations and synergies. Third, they have to maintain, as central outcomes of interest, the major objectives—what we call ‘value’ in this paper—of health systems commonly agreed on,5–7 notably: improving health and its distribution at the level of the population, providing financial risk protection efficiently (accounting for budget constraints),8 and increasing the satisfaction of citizens, while potentially acknowledging the positive implications that a healthier population may have on healthcare and the broader economy.9 Fourth, they should clearly articulate the comparators and counterfactuals pertaining to HSS interventions: whether an HSS intervention (eg, workforce training) is compared with another HSS intervention (eg, improving the drug supply chain) or with the status quo. Last, evaluation of multiple outcomes (eg, health, distribution of health, financial risk protection) raises the question of how to weigh each of these outcomes against one another and whether to produce an aggregated summary value or to maintain a dashboard of outcomes.
Collectively, these considerations imply that economic evaluations of HSS interventions will require developing new analytic models of health systems which: (1) acknowledge the dynamic connections between the different components of the health system and the policy levers acting on them, as well as characterise the type and interlinks of the system’s delivery platforms—that is, quantify the dynamic interactions between major health system components and (2) recognise the multiple constraints both within and outside the health sector which limit the system’s capacity to efficiently attain its objectives—that is, incorporate the constraints limiting the delivery of health to populations.
In illustrating such priority health system modelling (HSM) research areas for conducting economic evaluations of HSS interventions, we keep in mind the following major analytical question: how to identify good value (ie, greater health, distribution of health, or financial risk protection) for money (ie, per budget expenditure) investments in HSS?